The performance of Information Retrieval Systems (IRSs) is usually measured using two different c... more The performance of Information Retrieval Systems (IRSs) is usually measured using two different criteria, precision and recall. In such a way, the problem of tuning an IRS may be considered as a multi-objective optimization problem. In this contribution, we focus on the automatic learning of Boolean queries in IRSs by means of multi-objective evolutionary techniques. We present a comparative study of four multi-objective evolutionary optimization techniques of general-purpose (NSGA-II, SPEA2 and two MOGLS) to learn Boolean queries.
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2007
Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some p... more Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some problems of loss of information and lack of precision when working with discrete linguistic expression domains or when applying approximation operations in the symbolic aggregation methods. In this paper, we present a new IRS model based on the 2-tuple fuzzy linguistic approach, which allows us to overcome the problems of ordinal fuzzy linguistic IRSs and improve their performance.
Resumen—En este trabajo se presenta el diseño de un sistema de recomendaciones lingüístico difuso... more Resumen—En este trabajo se presenta el diseño de un sistema de recomendaciones lingüístico difuso para facilitar a los alumnos el acceso a información sobre recursos docentes que puedan ser de su interés. Al sugerir material didáctico adecuado a las necesidades específicas del alumno, se fomenta un aprendizaje significativo, incidiendo directamente en el proceso de enseñanza- aprendizaje. El uso de dicho
ABSTRACT A new instrument: IN-RECS is presented as the last Index to know impact factor in spanis... more ABSTRACT A new instrument: IN-RECS is presented as the last Index to know impact factor in spanish social sciences journals.
The performance of Information Retrieval Systems (IRSs) is usually measured using two different c... more The performance of Information Retrieval Systems (IRSs) is usually measured using two different criteria, precision and recall. In such a way, the problem of tuning an IRS may be considered as a multi-objective optimization problem. In this contribution, we focus on the automatic learning of Boolean queries in IRSs by means of multi-objective evolutionary techniques. We present a comparative study of four multi-objective evolutionary optimization techniques of general-purpose (NSGA-II, SPEA2 and two MOGLS) to learn Boolean queries.
The performance of Information Retrieval Systems (IRSs) is usually measured using two different c... more The performance of Information Retrieval Systems (IRSs) is usually measured using two different criteria, precision and recall. In such a way, the problem of tuning an IRS may be considered as a multi-objective optimization problem. In this contribution, we focus on the automatic learning of Boolean queries in IRSs by means of multi-objective evolutionary techniques. We present a comparative study of four multi-objective evolutionary optimization techniques of general-purpose (NSGA-II, SPEA2 and two MOGLS) to learn Boolean queries.
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2007
Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some p... more Information Retrieval Systems (IRSs) based on an ordinal fuzzy linguistic approach present some problems of loss of information and lack of precision when working with discrete linguistic expression domains or when applying approximation operations in the symbolic aggregation methods. In this paper, we present a new IRS model based on the 2-tuple fuzzy linguistic approach, which allows us to overcome the problems of ordinal fuzzy linguistic IRSs and improve their performance.
Resumen—En este trabajo se presenta el diseño de un sistema de recomendaciones lingüístico difuso... more Resumen—En este trabajo se presenta el diseño de un sistema de recomendaciones lingüístico difuso para facilitar a los alumnos el acceso a información sobre recursos docentes que puedan ser de su interés. Al sugerir material didáctico adecuado a las necesidades específicas del alumno, se fomenta un aprendizaje significativo, incidiendo directamente en el proceso de enseñanza- aprendizaje. El uso de dicho
ABSTRACT A new instrument: IN-RECS is presented as the last Index to know impact factor in spanis... more ABSTRACT A new instrument: IN-RECS is presented as the last Index to know impact factor in spanish social sciences journals.
The performance of Information Retrieval Systems (IRSs) is usually measured using two different c... more The performance of Information Retrieval Systems (IRSs) is usually measured using two different criteria, precision and recall. In such a way, the problem of tuning an IRS may be considered as a multi-objective optimization problem. In this contribution, we focus on the automatic learning of Boolean queries in IRSs by means of multi-objective evolutionary techniques. We present a comparative study of four multi-objective evolutionary optimization techniques of general-purpose (NSGA-II, SPEA2 and two MOGLS) to learn Boolean queries.
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Papers by A. Lopezherrera